Because these large generative models have been developed very recently (within the last five years), and have only recently become valuable to deploy from an economic perspective, no standards for the safe deployment of these systems exist. This lack of standards compounds the problems caused by the four distinguishing features of generative models we identify in Section , as well as the safety issues discussed above. At the same time, there's a growing field of research oriented around identifying the weaknesses of these models, as well as potential problems with their associated development practices [1]}, [2]}, [3]}, [4]}, [5]}, [6]}, [7]}, [8]}, [9]}. However, this research is not yet embodied in the form of repeatable standards that developers can adopt, though there are some critical and important steps in this direction (e.g., through the use of model cards [10]} and data sheets [11]} to document the capabilities, drawbacks, and other salient details of models). This lack of standards makes it both more challenging to deploy systems, as developers may need to determine their own policies for deployment, and it also makes deployments inherently risky, as there's less shared knowledge about what 'safe' deployments look like. We are, in a sense, building the plane as it is taking off.
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